WO2018201977A1 - 查勘任务分配方法、系统、服务器和存储介质 - Google Patents

查勘任务分配方法、系统、服务器和存储介质 Download PDF

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Publication number
WO2018201977A1
WO2018201977A1 PCT/CN2018/084758 CN2018084758W WO2018201977A1 WO 2018201977 A1 WO2018201977 A1 WO 2018201977A1 CN 2018084758 W CN2018084758 W CN 2018084758W WO 2018201977 A1 WO2018201977 A1 WO 2018201977A1
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Prior art keywords
surveyor
report information
survey
location
insurance report
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PCT/CN2018/084758
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English (en)
French (fr)
Inventor
刘金萍
洪旭栓
饶怡骏
林峰
林佩珊
范思焯
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平安科技(深圳)有限公司
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Publication of WO2018201977A1 publication Critical patent/WO2018201977A1/zh

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/08Insurance
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063Operations research, analysis or management
    • G06Q10/0631Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06311Scheduling, planning or task assignment for a person or group
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063Operations research, analysis or management
    • G06Q10/0631Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06312Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling

Definitions

  • the present application relates to a survey task distribution method, system, server and storage medium.
  • a survey task assignment method system, server, and medium are provided.
  • a method for assigning survey tasks including:
  • a survey task distribution system comprising:
  • a client terminal configured to obtain auto insurance report information, and upload the auto insurance report information to a server, where the auto insurance report information includes a place of risk;
  • a server configured to generate a survey task according to the vehicle insurance report information; identify a service type corresponding to the vehicle insurance report information; and query, according to the risk location, a surveyor identifier corresponding to the service type within a preset range; The task is sent to the survey terminal corresponding to the surveyor identification.
  • a server comprising a memory and one or more processors, the memory storing computer readable instructions, the computer readable instructions being executed by the processor, causing the one or more processors to perform the following step:
  • One or more non-transitory computer readable storage mediums storing computer readable instructions, when executed by one or more processors, cause one or more processors to perform the steps of:
  • 1 is an application environment diagram of a survey task assignment method according to one or more embodiments
  • FIG. 2 is a flow chart of a method for assigning survey tasks in accordance with one or more embodiments
  • FIG. 3 is a block diagram of a survey task distribution system in accordance with one or more embodiments.
  • FIG. 4 is a block diagram of a server in accordance with yet another embodiment.
  • the car insurance claim data analysis method provided in the embodiment of the present application can be applied to the application environment as shown in FIG.
  • the client terminal 102 is connected to the server 104 via a network.
  • the survey terminal 106 is connected to the server 104 via a network.
  • the server 104 generates a survey task based on the vehicle insurance report information.
  • the server 104 compares the vehicle insurance report information with the preset rule, and identifies the service type corresponding to the vehicle insurance report information.
  • the server 104 searches for the service point name within the preset range from the insurance location, and queries the surveyor identifier corresponding to the required surveyer level query according to the service point name.
  • the server 104 sends the survey task to the survey terminal 106 corresponding to the surveyor identification. Since the server directly searches for the corresponding surveyor identification within the preset range according to the service type corresponding to the vehicle insurance report information, the survey task can be assigned to the appropriate surveyor for survey, thereby effectively saving the surveyor. The dispatching time-consuming, and thus effectively improve the efficiency of surveying vehicle accidents.
  • a method for assigning a survey task is provided.
  • the method is applied to the server as an example, and specifically includes the following steps:
  • Step 202 Receive auto insurance report information uploaded by the client terminal, where the auto insurance report information includes a risk location.
  • Step 204 Generate a survey task according to the vehicle insurance report information.
  • the customer can use the client terminal to report the vehicle to the server.
  • the auto insurance report information includes the basic information of the vehicle, the place of the accident and the cause of the accident.
  • the server After receiving the vehicle insurance report information, the server generates a corresponding survey task according to the vehicle insurance report information.
  • the survey information carries the basic information of the vehicle and the place of the accident.
  • Step 206 Identify a service type corresponding to the vehicle insurance report information.
  • the server compares the auto insurance report information with the preset rule to identify the service type corresponding to the auto insurance report information.
  • the types of services corresponding to the auto insurance report information include: general accidents, major accidents and mega-accidents. Different business types can have different preset rules.
  • the information on the auto insurance report includes the basic information of the vehicle, the cause of the accident, the place of the accident, whether it is reported on the spot, and whether it is out of danger.
  • the default rules include: on-site reporting, non-off-site insurance, and the location of the insurance does not include preset keywords.
  • Table 1 The default rules are as shown in Table 1 below:
  • the server can identify whether the vehicle accident is a general accident. If it is determined that the vehicle accident is a general accident, the service type corresponding to the vehicle insurance report information is a general accident.
  • Step 208 Query, according to the risk location, the surveyor identifier corresponding to the service type in the preset range.
  • Step 210 Send the survey task to the survey terminal corresponding to the survey identifier.
  • the server looks up the appropriate surveyor within the preset range of the location of the accident. Specifically, the server converts the textual description of the location of the insurance and the address of the plurality of service points into geographic coordinates in the electronic map. The server searches the electronic map for the service point name within the preset range according to the geographic coordinates corresponding to the risk location.
  • the preset range can be the same administrative area, such as Nanshan District. The preset range can also be a preset distance, such as 10 kilometers.
  • the server can search for the nearest service point from the safe place within the preset range according to the geographical coordinates corresponding to the risk location. name.
  • Each service point is equipped with multiple surveyors.
  • the surveyor has a unique surveyer's logo, and the surveyor's logo has the corresponding surveyor level. Different surveyor levels can be used to investigate vehicle types of business types.
  • the step of querying the surveyor identifier corresponding to the service type in the preset range according to the risk location includes: obtaining the surveyor level corresponding to the service type; and searching for the service point name in the preset scope according to the risk location According to the service point name and the surveyor level query corresponding to the surveyor identification.
  • the database of the server stores the matching table of the service type of the vehicle insurance report information and the surveyor level.
  • the match list records the level of the surveyor corresponding to the type of business of the auto insurance report information. Among them, the more complex the type of business, the higher the level of the surveyor required, and the simpler the type of business, the lower the level of the surveyor required.
  • the matching table also records the corresponding surveyor identification, the service point name to which the surveyor belongs, and the service point address.
  • the surveyor level corresponding to the type of business may also be referred to as the required surveyor level.
  • the server After searching for the corresponding service point name, the server queries the corresponding surveyer identifier in the matching table according to the service point name and the required surveyer level. The server sends the survey task to the survey terminal corresponding to the surveyor identifier. Since the server directly searches for the corresponding surveyor identification within the preset range according to the service type corresponding to the vehicle insurance report information, the survey task can be assigned to the appropriate surveyor for investigation, thereby avoiding the assignment of the survey task. Unreasonable, it is necessary to carry out the adjustment of the dispatcher's dispatch, so that the dispatcher's dispatching time can be effectively saved.
  • the vehicle inspection report information is used to generate a corresponding survey task.
  • the inspection task can be assigned to the appropriate surveyor without the need for manual participation after receiving the vehicle insurance report information.
  • the problem of unsuccessful allocation of surveying tasks is needed to avoid the dispatching of dispatchers, which can effectively save the dispatching time of the surveyors, and thus can effectively improve the efficiency of surveying vehicle accidents.
  • steps in the flowchart of FIG. 2 are sequentially displayed as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Except as explicitly stated herein, the execution of these steps is not strictly limited, and the steps may be performed in other orders. Moreover, at least some of the steps in FIG. 2 may include a plurality of sub-steps or stages, which are not necessarily performed at the same time, but may be executed at different times, the execution of these sub-steps or stages The order is also not necessarily sequential, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of the other steps.
  • the method further includes: performing big data analysis on the vehicle insurance report information from different client terminals to obtain an accident high-risk location; and generating prompt information for adjusting the number of surveyors in the preset range according to the high-incident location of the accident.
  • the server can perform big data analysis on the auto insurance information according to the preset frequency, thereby obtaining a high incidence location of the accident.
  • the preset frequency can be once a month, once a quarter, or once a year.
  • the step of performing big data analysis on vehicle insurance report information from different client terminals includes: obtaining a place of risk in the car insurance report information; performing big data analysis on the multiple risk locations; if at the same risk location If the number of accidents exceeds the preset number of accidents, the location of the accident is recorded as the location of the accident.
  • the server obtains the risk location in the massive auto insurance report information, and performs big data analysis on multiple insurance locations. Big data analysis can employ cluster analysis algorithms, such as the K-means algorithm.
  • the vehicle insurance report information is used as a data set, and the data set is divided into a plurality of different categories. The categories include the location of the insurance, the license plate number and the location of the accident.
  • the itinerary calculation is carried out as the data object, and the number of times of the risk of the same risk location is obtained.
  • Two or more destinations within the preset range of the same road segment may be considered as the same place of danger. For example, the preset range can be 1 km. If the number of accidents in the same place of risk exceeds the preset number of times of risk, the server records the location of the accident as the location of the accident.
  • the step of generating prompt information for adjusting the number of surveyors in the preset range according to the high-incident location of the accident includes: counting the service type and quantity of the auto insurance report information of the high-incident location; The number of the corresponding vehicle insurance report information is calculated by the surveyor level corresponding to the surveyor's demand quantity; the current number of the surveyor corresponding to the surveyor level is obtained within the preset range of the accident high-incidence location; and the survey surveyor is generated according to the survey surveyer's demand quantity and the current surveyor's current quantity. The number of tips to adjust the information.
  • the server After the big data analysis has obtained the high-incidence location of the accident, the server will collect statistics on the auto insurance report information of each high-incident location. Specifically, the service type and quantity statistics of the server for the vehicle insurance report information, and the number of vehicle insurance report information corresponding to each service type. Since different types of vehicle accidents require different levels of surveyors to go to the accident site survey, the server can determine the number of surveyor requirements corresponding to each surveyer level according to the number of vehicle insurance report information corresponding to each type of service.
  • the prompt information is sent to the management terminal. In order for managers to adjust the number of surveyors in a timely manner.
  • the server can also search for the number of service points within the preset range of the incident. If the number of service points in the preset range is 1, the number of surveyors in the service point can be adjusted according to the above method. If the number of service points in the preset range is greater than 1, the number of surveyors in the service point can be adjusted in various ways. For example, the server may allocate the above-mentioned calculated surveyor demand quantity to multiple service points according to a preset ratio according to the service point address and the location of the accident high-risk location. The closer to the height of the accident, the higher the preset ratio. The server may also perform the mean calculation of the number of surveyor requirements calculated above and the number of service points, and obtain the number of surveyor requirements corresponding to each service point.
  • the method further comprises: performing big data analysis on the vehicle insurance report information from different client terminals to obtain a high-risk insurance location; and when receiving the vehicle insurance report information carrying the high-risk insurance location, generating and verifying whether to swindle The prompt information; the prompt information and the survey task are sent to the survey terminal corresponding to the survey target.
  • the server will analyze the auto insurance report information from different customer terminals according to the preset frequency to obtain high-risk locations.
  • the step of performing big data analysis on the vehicle insurance report information from different client terminals includes: obtaining the license plate number, the place of the insurance, and the cause of the risk in the vehicle insurance report information; and the location of the risk corresponding to the plurality of license plate numbers and The reason for the risk is to conduct big data analysis; the cause of the risk includes intentional manufacturing site; the reason for obtaining the risk is the characteristic of the place of the insurance corresponding to the car accident case on the intentional manufacturing site; if the risk location with the same characteristics and the reason for the risk is the number of car accident cases on the intentional manufacturing site When the amount is larger than the preset case, the characteristics of the place of the accident are recorded, and the location of the risk is recorded as a high-risk place.
  • the server obtains the risk factor for the risk location corresponding to the car accident case on the intentional manufacturing site.
  • Features include: road teeth, shoulders, road piles and columns. Due to the partial fraud insurance auto insurance claims, the accident scene will be intentionally created at the location with the above characteristics. If the risk location with the same characteristics and the reason for the risk is that the number of auto accident cases on the intentional manufacturing site is greater than the preset case amount, the server records the characteristics of the risk location and records the risk location with the feature as a high risk insurance location. If there is a risky high-risk location in the auto insurance report information, it means that there is a possibility of fraudulent insurance.
  • the server When the server receives the high-risk insurance location in the vehicle insurance report information, the server generates a prompt to verify whether the fraud is guaranteed.
  • the server sends the prompt information and the survey task to the survey terminal corresponding to the surveyer identifier. Therefore, the survey personnel can verify whether there is a false vehicle accident of fraudulent insurance at the scene of the accident investigation, thereby effectively reducing the automobile insurance loss of the insurance company.
  • the method further includes: performing statistics on the plurality of survey tasks corresponding to the surveyer identifier; and querying the surveyor corresponding to the surveyer identifier according to the statistical result Level adjustments.
  • the server may adjust the level of the surveyor.
  • the server may perform statistics on multiple survey tasks corresponding to the surveyor identification at regular intervals, thereby obtaining the number of survey tasks performed by each surveyor in a fixed time.
  • the fixed time can be one quarter, or half a year or one year.
  • the server can configure corresponding weights for the survey task according to the service type corresponding to the auto insurance report information. Different survey tasks can be configured with different weights.
  • the server calculates the number of the survey tasks for each surveyor identification and the weight corresponding to the survey task in a fixed time, and obtains the statistical weight corresponding to the surveyer identifier.
  • the surveyor level has a corresponding weight range, and the server compares the statistical weight corresponding to each surveyer identifier with the weight range, thereby obtaining the corresponding surveyor level.
  • a survey task distribution system including: a client terminal 302, a server 304, and a survey terminal 306, wherein:
  • the client terminal 302 is configured to obtain auto insurance report information, upload the auto insurance report information to the server, and the auto insurance report information includes the risk location.
  • the server 304 is configured to generate a survey task according to the vehicle insurance report information; identify a service type corresponding to the vehicle insurance report information; and query the surveyor identifier corresponding to the service type within the preset range according to the risk location; and send the survey task to the survey corresponding to the survey target identifier Terminal 306.
  • the server 304 is further configured to perform big data analysis on the vehicle insurance report information from different client terminals to obtain an accident high-risk location; and generate prompt information for adjusting the number of surveyors in the preset range according to the high-incident location of the accident. Sending the prompt information to the management terminal 308.
  • the server 304 is further configured to perform statistics on the service type and quantity of the vehicle insurance report information of the accident-prone location; and calculate the demand quantity of the surveyor corresponding to the surveyor level according to the number of the vehicle insurance report information corresponding to the service type; The current number of surveyors corresponding to the surveyor level within the preset range of the accident occurrence location; the prompt information for adjusting the number of surveyors is generated according to the number of survey surveyers and the current number of surveyors.
  • the server 304 is further configured to perform big data analysis on the vehicle insurance report information from different client terminals to obtain a high-risk insurance location; and when receiving the vehicle insurance report information carrying the high-risk insurance location, generate and verify whether to swindle The prompt information; the prompt information and the survey task are sent to the survey terminal 302 corresponding to the survey identifier.
  • the surveyor identification has a corresponding surveyor level
  • the server 304 is further configured to obtain a surveyor level corresponding to the service type; and search for a service point name within a preset range according to the risk location; according to the service point name and the survey
  • the level of the inspector corresponds to the surveying inspector's logo; the surveying tasks corresponding to the inspector's logo are counted; and the level of the surveyor corresponding to the surveyor's logo is adjusted according to the statistical result.
  • a server including a processor coupled via a system bus, memory, computer readable instructions stored on the memory and executable on the processor, and a network interface Wait.
  • the processor is used to provide calculation and control capabilities.
  • the memory of the server includes a non-volatile storage medium and an internal memory.
  • the non-volatile storage medium stores an operating system, computer readable instructions, and a database.
  • the internal memory provides an environment for operation of an operating system and computer readable instructions in a non-volatile storage medium.
  • the non-volatile storage medium can be a non-transitory computer readable storage medium.
  • a method of assigning a survey task is implemented when the processor executes computer readable instructions.
  • the network interface is used to communicate with the client terminal over a network connection.
  • the server can be implemented as a standalone server or a server cluster consisting of multiple servers. It will be understood by those skilled in the art that the structure shown in FIG. 4 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the server to which the solution of the present application is applied.
  • the specific server may include a ratio. More or fewer components are shown in the figures, or some components are combined, or have different component arrangements.
  • a server comprising a memory and one or more processors having stored therein computer readable instructions that, when executed by a processor, cause one or more processors to perform the above The steps in the various method embodiments.
  • non-volatile storage media having computer readable instructions that, when executed by one or more processors, cause one or more processors to perform each of The steps in the method embodiments.
  • Non-volatile memory can include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory.
  • Volatile memory can include random access memory (RAM) or external cache memory.
  • RAM is available in a variety of formats, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronization chain.
  • SRAM static RAM
  • DRAM dynamic RAM
  • SDRAM synchronous DRAM
  • DDRSDRAM double data rate SDRAM
  • ESDRAM enhanced SDRAM
  • Synchlink DRAM SLDRAM
  • Memory Bus Radbus
  • RDRAM Direct RAM
  • DRAM Direct Memory Bus Dynamic RAM
  • RDRAM Memory Bus Dynamic RAM

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Abstract

一种查勘任务分配方法,包括:接收客户终端上传的车险报案信息,车险报案信息包括出险地点;根据车险报案信息生成查勘任务;识别车险报案信息对应的业务类型;根据出险地点查询预设范围内与业务类型对应的查勘员标识;将查勘任务发送至查勘员标识对应的查勘终端。

Description

查勘任务分配方法、系统、服务器和存储介质
本申请要求于2017年5月5日提交中国专利局,申请号为2017103134124,申请名称为“查勘任务分配方法、系统、服务器和介质”的中国专利申请的优先权,其全部内容通过引用结合在本申请中。
技术领域
本申请涉及一种查勘任务分配方法、系统、服务器和存储介质。
背景技术
随着汽车的普及,车险也逐渐融入到人们的生活中。当被保险的车辆发生交通事故时,保险公司会派遣查勘员前往事故现场进行查勘。在传统的方式中,是通过排班表的方式按照预先排好的班次来派遣查勘员。查勘员的经验越丰富,查勘效率会越高。如果遇到较为复杂的事故,而且按照排班表将该事故分配给经验较少的查勘员时,需要对查勘员进行人员派遣调整。而人员派遣调整通过需要依赖人工操作,这使得查勘员的派遣安排耗时较长,导致事故查勘效率降低。
发明内容
根据本申请公开的各种实施例,提供一种查勘任务分配方法、系统、服务器和介质。
一种查勘任务分配方法,包括:
接收客户终端上传的车险报案信息,所述车险报案信息包括出险地点;
根据所述车险报案信息生成查勘任务;
识别所述车险报案信息对应的业务类型;
根据所述出险地点查询预设范围内与所述业务类型对应的查勘员标识;及
将所述查勘任务发送至所述查勘员标识对应的查勘终端。
一种查勘任务分配系统,包括:
客户终端,用于获取车险报案信息,将所述车险报案信息上传至服务器,所述车险报案信息包括出险地点;及
服务器,用于根据所述车险报案信息生成查勘任务;识别所述车险报案信息对应的业务类型;根据所述出险地点查询预设范围内与所述业务类型对应的查勘员标识;将所述查勘任务发送至所述查勘员标识对应的查勘终端。
一种服务器,包括存储器和一个或多个处理器,所述存储器中储存有计算机可读指令,所述计算机可读指令被所述处理器执行时,使得所述一个或多个处理器执行以下步骤:
接收客户终端上传的车险报案信息,所述车险报案信息包括出险地点;
根据所述车险报案信息生成查勘任务;
识别所述车险报案信息对应的业务类型;
根据所述出险地点查询预设范围内与所述业务类型对应的查勘员标识;及
将所述查勘任务发送至所述查勘员标识对应的查勘终端。
一个或多个存储有计算机可读指令的非易失性计算机可读存储介质,计算机可读指令被一个或多个处理器执行时,使得一个或多个处理器执行以下步骤:
接收客户终端上传的车险报案信息,所述车险报案信息包括出险地点;
根据所述车险报案信息生成查勘任务;
识别所述车险报案信息对应的业务类型;
根据所述出险地点查询预设范围内与所述业务类型对应的查勘员标识;及
将所述查勘任务发送至所述查勘员标识对应的查勘终端。
本申请的一个或多个实施例的细节在下面的附图和描述中提出。本申请的其它特征和优点将从说明书、附图以及权利要求书变得明显。
附图说明
为了更清楚地说明本申请实施例中的技术方案,下面将对实施例中所需要使用的附图作简单地介绍,显而易见地,下面描述中的附图仅仅是本申请的一些实施例,对于本领域普通技术人员来讲,在不付出创造性劳动的前提下,还可以根据这些附图获得其它的附图。
图1为根据一个或多个实施例中的查勘任务分配方法应用环境图;
图2为根据一个或多个实施例中查勘任务分配方法的流程图;
图3为根据一个或多个实施例中查勘任务分配系统的框图;
图4为根据又一个实施例中服务器的框图。
具体实施方式
为了使本申请的目的、技术方案及优点更加清楚明白,以下结合附图及实施例,对本申请进行进一步详细说明。应当理解,此处描述的具体实施例仅仅用以解释本申请,并不用于限定本申请。
本申请实施例中所提供的车险理赔数据分析方法,可以应用于如图1所示的应用环境中。客户终端102通过网络与服务器104连接。查勘终端106通过网络与服务器104连接。当车辆发生事故时,客户可以利用客户终端102向服务器104进行车险报案。服务器104根据车险报案信息生成查勘任务。服务器104将车险报案信息与预设规则进行比对,识别车险报案信息对应的业务类型。服务器104将出险地点搜索预设范围内的服务点名称,根据服务点名称与所需查勘员级别查询对应的查勘员标识。服务器104将查勘任务发送至该查勘员标识对应的查勘终端106。由于服务器直接根据车险报案信息对应的业务类型,即可在在预设范围内查询到相应的查勘员标识,由此能够使得查勘任务被分配至合适的查勘员进行查勘,从而能够有效节省查勘员的派遣耗时,进而有效提高车辆事故的查勘效率。
在一个实施例中,如图2所示,提供了一种查勘任务分配方法,以该方 法应用于服务器为例进行说明,具体包括以下步骤:
步骤202,接收客户终端上传的车险报案信息,车险报案信息包括出险地点。
步骤204,根据车险报案信息生成查勘任务。
当车辆发生事故时,客户可以利用客户终端向服务器进行车险报案。车险报案信息包括车辆基本信息、出险地点和出险原因等。服务器接收到车险报案信息后,根据车险报案信息生成相应的查勘任务。查勘任务中携带了车辆基本信息和出险地点等。
步骤206,识别车险报案信息对应的业务类型。
服务器将车险报案信息与预设规则进行比对,以便识别车险报案信息对应的业务类型。车险报案信息对应的业务类型包括:一般事故、重大事故和特大事故等。不同的业务类型可以有不同的预设规则。车险报案信息包括车辆基本信息、出险原因、出险地点、是否现场报案和是否异地出险等。以一般事故为例,预设规则包括:现场报案、非异地出险、出险地点不包含预设关键字。预设规则如下表一所示:
表一:
现场报案
高速公路
出险原因 行驶受损
出险地点不包含关键字 高架桥、立交桥、隧道、隧洞
承保险别 车损险
报案损失类型 标的车损、三者车损
出险地点 南山区、龙华区
车辆能否正常行驶
经过比对之后,服务器可以识别出本次车辆事故是否为一般事故。若确定本次车辆事故为一般事故,则本次车险报案信息对应的业务类型即为一般事故。
步骤208,根据出险地点查询预设范围内与业务类型对应的查勘员标识。
步骤210,将查勘任务发送至查勘员标识对应的查勘终端。
为了能够及时分配查勘任务,服务器在出险地点的预设范围内查找适当的查勘员。具体的,服务器将出险地点以及多个服务点地址的文字描述转换为电子地图中的地理坐标。服务器根据出险地点对应的地理坐标在电子地图中搜索预设范围内的服务点名称。预设范围可以是同一个行政区域,如南山区。预设范围也可以是预设距离,如10公里。若预设范围内存在多个服务点名称,为了进一步节省查勘员前往出险地点的耗时,提高查勘效率,服务器可以根据出险地点对应的地理坐标在预设范围内搜索距离出险地点最近的服务点名称。
每个服务点都配备了多名查勘员。查勘员具有唯一的查勘员标识,查勘员标识具有对应的查勘员级别。不同的查勘员级别可以查勘业务类型的车辆事故。
在其中一个实施例中,根据出险地点查询预设范围内与业务类型对应的查勘员标识的步骤,包括:获取与业务类型对应的查勘员级别;根据出险地点搜索预设范围内的服务点名称;根据服务点名称与查勘员级别查询对应的查勘员标识。
服务器的数据库中存储了车险报案信息的业务类型与查勘员级别的匹配表。该匹配表中记录了与车险报案信息的业务类型相对应的查勘员级别。其中,业务类型越复杂所需要的查勘员级别越高,业务类型越简单所需要的查勘员级别越低。匹配表中除了记录车险报案信息的业务类型与查勘员级别的对应关系之外,还记录了对应的查勘员标识、查勘员所属的服务点名称以及服务点地址等。与业务类型对应的查勘员级别也可以称为所需查勘员级别。服务器在搜索到相应的服务点名称之后,根据服务点名称与所需查勘员级别在匹配表中查询对应的查勘员标识。服务器将查勘任务发送至该查勘员标识对应的查勘终端。由于服务器直接根据车险报案信息对应的业务类型,即可在在预设范围内查询到相应的查勘员标识,由此能够使得查勘任务被分配至 合适的查勘员进行查勘,避免了因查勘任务分配不合理而需要进行查勘员派遣调整的问题,从而能够有效节省查勘员的派遣耗时。
本实施例中,在接收到车险报案信息之后,利用车险报案信息生成相应的查勘任务。通过识别车险报案信息对应的业务类型,由此可以根据出险地点查询预设范围内与业务类型对应的查勘员标识,从而能够将查勘任务分配至合适的查勘员进行现场查勘。在整个过程中,在接到车险报案信息后不需要人工参与,即可将查勘任务分配给合适的查勘员。避免了因查勘任务分配不合理而需要进行查勘员派遣调整的问题,能够有效节省查勘员的派遣耗时,进而能够有效提高车辆事故的查勘效率。
应该理解的是,虽然图2的流程图中的各个步骤按照箭头的指示依次显示,但是这些步骤并不是必然按照箭头指示的顺序依次执行。除非本文中有明确的说明,这些步骤的执行并没有严格的顺序限制,这些步骤可以以其它的顺序执行。而且,图2中的至少一部分步骤可以包括多个子步骤或者多个阶段,这些子步骤或者阶段并不必然是在同一时刻执行完成,而是可以在不同的时刻执行,这些子步骤或者阶段的执行顺序也不必然是依次进行,而是可以与其它步骤或者其它步骤的子步骤或者阶段的至少一部分轮流或者交替地执行。
在一个实施例中,该方法还包括:对来自不同客户终端的车险报案信息进行大数据分析,得到事故高发地点;根据事故高发地点生成对预设范围内的查勘员数量进行调整的提示信息。
本实施例中,服务器可以按照预设频率对车险保险信息进行大数据分析,以此得到事故高发地点。预设频率可以是一个月一次,也可以一个季度一次,也可以是一年一次。
在一个实施例中,对来自不同客户终端的车险报案信息进行大数据分析的步骤,包括:获取车险报案信息中的出险地点;对多个出险地点进行大数据分析;若在同一个出险地点的出险次数超过预设出险次数,则将出险地点记录为事故高发地点。
服务器在海量的车险报案信息中获取出险地点,对多个出险地点进行大数据分析。大数据分析可以采用聚类分析算法,例如,K-means算法等。利用车险报案信息作为数据集合,将该数据集合分成多个不同类别。类别包括出险地点、车牌号和出险地点等。将出险地点作为数据对象进行迭代计算,得到同一个出险地点的出险次数。在同一路段的预设范围内的两个或两个以上的出险地点可以视为同一个出险地点。例如,预设范围可以是1公里。如果在同一个出险地点的出险次数超过预设出险次数,则服务器将该出险地点记录为事故高发地点。
由于事故高发地点的出险次数较多,为了能够及时对车辆事故进行查勘处理,需要对预设范围内的查勘员数量进行调整。在其中一个实施例中,根据事故高发地点生成对预设范围内的查勘员数量进行调整的提示信息的步骤,包括:对事故高发地点的车险报案信息的业务类型和数量进行统计;根据业务类型对应的车险报案信息的数量计算查勘员级别对应的查勘员需求数量;获取事故高发地点预设范围内查勘员级别对应的查勘员当前数量;根据查勘员需求数量与查勘员当前数量生成对查勘员数量进行调整的提示信息。
服务器在大数据分析得到事故高发地点后,对每个事故高发地点的车险报案信息进行统计。具体的,服务器对车险报案信息的业务类型和数量统计,以及每种业务类型对应的车险报案信息的数量。由于不同业务类型的车辆事故需要不同级别的查勘员前往事故现场查勘,因此服务器可以根据每种业务类型对应的车险报案信息的数量确定每一个查勘员级别对应的查勘员需求数量。获取事故高发地点预设范围内每个查勘员级别对应的查勘员当前数量,根据查勘员需求数量与查勘员当前数量对预设范围内所需的查勘员数量生成相应的调整提示信息,将该提示信息发送至管理终端。以便管理人员能够对查勘员数量及时进行调整。
进一步的,为了使得每个服务点的查勘员数量配置更优化。服务器还可以搜索事故高发地点预设范围内的服务点数量。若预设范围内的服务点数量为1,则该服务点内的查勘员数量可以根据上述方式进行调整。若预设范围 内的服务点数量大于1,则可以采用多种方式对服务点内的查勘员数量进行调整。例如,服务器可以根据服务点地址与事故高发地点的远近,按照预设比例将上述计算得到的查勘员需求数量分配至多个服务点。距离事故高发地点越近,预设比例越高。服务器还可以将上述计算得到的查勘员需求数量与服务点数量进行均值计算,得到每个服务点对应的查勘员需求数量。
在一个实施例中,该方法还包括:对来自不同客户终端的车险报案信息进行大数据分析,得到高风险出险地点;当接收到携带高风险出险地点的车险报案信息时,生成核实是否骗保的提示信息;将提示信息与查勘任务发送至查勘员标识对应的查勘终端。
为了避免车险骗保带给保险公司的损失,服务器会按照预设频率对来自不同客户终端的车险报案信息进行大数据分析,得到高风险地点。在其中一个实施例中,对来自不同客户终端的车险报案信息进行大数据分析的步骤,包括:获取车险报案信息中的车牌号、出险地点和出险原因;对多个车牌号对应的出险地点和出险原因进行大数据分析;出险原因包括故意制造现场;获取出险原因为故意制造现场的车险案件所对应的出险地点的特征;若具有相同特征的出险地点且出险原因为故意制造现场的车险案件数量大于预设案件量时,则记录出险地点的特征,并将具有特征的出险地点记录为高风险出险地点。
服务器获取出险原因为故意制造现场的车险案件所对应的出险地点的特征。特征包括:路牙、路肩、路桩和柱子等。由于部分骗保的车险理赔会在具有上述特征的地点故意制造事故现场。如果具有相同特征的出险地点且出险原因为故意制造现场的车险案件的数量大于预设案件量,服务器记录该出险地点的特征,并且将具有该特征的出险地点记录为高风险出险地点。如果在车险报案信息中出险高风险出险地点,则意味着存在骗保的可能性。
当服务器接收到车险报案信息中携带了高风险出险地点时,服务器生成核验是否骗保的提示信息。服务器将提示信息与查勘任务发送至查勘员标识对应的查勘终端。由此使得查勘人员在事故现场查勘时核验是否存在骗保的 虚假车辆事故,从而有效减少保险公司的车险损失。
在一个实施例中,在将查勘任务发送至查勘员标识对应的查勘终端的步骤之后,还包括:对查勘员标识对应的多个查勘任务进行统计;根据统计结果对查勘员标识对应的查勘员级别进行调整。
本实施例中,为了对查勘员进行有效的绩效考核,服务器可以对查勘员的级别进行调整。服务器可以每隔固定时间对查勘员标识对应的多个查勘任务进行统计,从而得到固定时间内每个查勘员所执行的查勘任务的数量。固定时间可以是一个季度,也可以是半年或一年等。服务器根据车险报案信息对应的业务类型可以对查勘任务配置相应的权重。不同的查勘任务可以配置不同的权重。服务器对固定时间内每个查勘员标识的查勘任务的数量和查勘任务对应的权重进行计算,得到查勘员标识对应的统计权重。查勘员级别具有相应的权重范围,服务器将每个查勘员标识对应的统计权重与权重范围进行比较,从而得到相应的查勘员级别。
在一个实施例中,如图3所示,提供了一种查勘任务分配系统,包括:客户终端302、服务器304和查勘终端306,其中:
客户终端302,用于获取车险报案信息,将车险报案信息上传至服务器,车险报案信息包括出险地点。
服务器304,用于根据车险报案信息生成查勘任务;识别车险报案信息对应的业务类型;根据出险地点查询预设范围内与业务类型对应的查勘员标识;将查勘任务发送至查勘员标识对应的查勘终端306。
在其中一个实施例中,服务器304还用于对来自不同客户终端的车险报案信息进行大数据分析,得到事故高发地点;根据事故高发地点生成对预设范围内的查勘员数量进行调整的提示信息;将提示信息发送至管理终端308。
在其中一个实施例中,服务器304还用于对事故高发地点的车险报案信息的业务类型和数量进行统计;根据业务类型对应的车险报案信息的数量计算查勘员级别对应的查勘员需求数量;获取事故高发地点预设范围内查勘员级别对应的查勘员当前数量;根据查勘员需求数量与查勘员当前数量生成对 查勘员数量进行调整的提示信息。
在一个实施例中,服务器304还用于对来自不同客户终端的车险报案信息进行大数据分析,得到高风险出险地点;当接收到携带高风险出险地点的车险报案信息时,生成核实是否骗保的提示信息;将提示信息与查勘任务发送至查勘员标识对应的查勘终端302。
在一个实施例中,查勘员标识具有对应的查勘员级别,服务器304还用于获取与业务类型对应的查勘员级别;根据出险地点搜索预设范围内的服务点名称;根据服务点名称与查勘员级别查询对应的查勘员标识;对查勘员标识对应的多个查勘任务进行统计;根据统计结果对查勘员标识对应的查勘员级别进行调整。
在一个实施例中,提供了一种服务器,如图4所示,该服务器包括通过系统总线连接的处理器、存储器、存储在存储器上并可在处理器上运行的计算机可读指令以及网络接口等。其中,处理器用于提供计算和控制能力。该服务器的存储器包括非易失性存储介质、内存储器。该非易失性存储介质存储有操作系统、计算机可读指令和数据库。该内存储器为非易失性存储介质中的操作系统和计算机可读指令的运行提供环境。非易失性存储介质可以是非易失性计算机可读存储介质。处理器执行计算机可读指令时实现一种查勘任务分配方法。网络接口用于据以与客户终端通过网络连接通信。该服务器可以用独立的服务器或者是多个服务器组成的服务器集群来实现。本领域技术人员可以理解,图4中示出的结构,仅仅是与本申请方案相关的部分结构的框图,并不构成对本申请方案所应用于其上的服务器的限定,具体的服务器可以包括比图中所示更多或更少的部件,或者组合某些部件,或者具有不同的部件布置。
在一个实施例中,提供了一种服务器,包括存储器和一个或多个处理器,存储器中储存有计算机可读指令,计算机可读指令被处理器执行时,使得一个或多个处理器执行上述各个方法实施例中的步骤。
在一个实施例中,提供了一个或多个存储有计算机可读指令的非易失性 存储介质,计算机可读指令被一个或多个处理器执行时,使得一个或多个处理器执行上述各个方法实施例中的步骤。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程,是可以通过计算机可读指令来指令相关的硬件来完成,所述的计算机可读指令可存储于一非易失性计算机可读取存储介质中,该计算机可读指令在执行时,可包括如上述各方法的实施例的流程。其中,本申请所提供的各实施例中所使用的对存储器、存储、数据库或其它介质的任何引用,均可包括非易失性、易失性存储器。非易失性存储器可包括只读存储器(ROM)、可编程ROM(PROM)、电可编程ROM(EPROM)、电可擦除可编程ROM(EEPROM)或闪存。易失性存储器可包括随机存取存储器(RAM)或者外部高速缓冲存储器。作为说明而非局限,RAM以多种形式可得,诸如静态RAM(SRAM)、动态RAM(DRAM)、同步DRAM(SDRAM)、双数据率SDRAM(DDRSDRAM)、增强型SDRAM(ESDRAM)、同步链路(Synchlink)DRAM(SLDRAM)、存储器总线(Rambus)直接RAM(RDRAM)、直接存储器总线动态RAM(DRDRAM)、以及存储器总线动态RAM(RDRAM)等。
以上实施例的各技术特征可以进行任意的组合,为使描述简洁,未对上述实施例中的各个技术特征所有可能的组合都进行描述,然而,只要这些技术特征的组合不存在矛盾,都应当认为是本说明书记载的范围。
以上实施例仅表达了本申请的几种实施方式,其描述较为具体和详细,但并不能因此而理解为对发明专利范围的限制。应当指出的是,对于本领域的普通技术人员来说,在不脱离本申请构思的前提下,还可以做出若干变形和改进,这些都属于本申请的保护范围。因此,本申请专利的保护范围应以所附权利要求为准。

Claims (20)

  1. 一种查勘任务分配方法,包括:
    接收客户终端上传的车险报案信息,所述车险报案信息包括出险地点;
    根据所述车险报案信息生成查勘任务;
    识别所述车险报案信息对应的业务类型;
    根据所述出险地点查询预设范围内与所述业务类型对应的查勘员标识;及
    将所述查勘任务发送至所述查勘员标识对应的查勘终端。
  2. 根据权利要求1所述的方法,其特征在于,所述方法还包括:
    对来自不同客户终端的车险报案信息进行大数据分析,得到事故高发地点;及
    根据所述事故高发地点生成对预设范围内的查勘员数量进行调整的提示信息。
  3. 根据权利要求2所述的方法,其特征在于,所述根据所述事故高发地点生成对预设范围内的查勘员数量进行调整的提示信息包括:
    对所述事故高发地点的车险报案信息的业务类型和数量进行统计;
    根据业务类型对应的车险报案信息的数量计算查勘员级别对应的查勘员需求数量;
    获取事故高发地点预设范围内查勘员级别对应的查勘员当前数量;及
    根据所述查勘员需求数量与所述查勘员当前数量生成对查勘员数量进行调整的提示信息。
  4. 根据权利要求1所述的方法,其特征在于,所述方法还包括:
    对来自不同客户终端的车险报案信息进行大数据分析,得到高风险出险地点;
    当接收到携带所述高风险出险地点的车险报案信息时,生成核实是否骗保的提示信息;及
    将所述提示信息与所述查勘任务发送至查勘员标识对应的查勘终端。
  5. 根据权利要求1所述的方法,其特征在于,所述查勘员标识具有对应的查勘员级别,所述根据所述出险地点查询预设范围内与所述业务类型对应的查勘员标识包括:
    获取与所述业务类型对应的查勘员级别;根据所述出险地点搜索预设范围内的服务点名称;根据所述服务点名称与所述查勘员级别查询对应的查勘员标识;
    在所述将所述查勘任务发送至所述查勘员标识对应的查勘终端之后,所述方法还包括:
    对所述查勘员标识对应的多个查勘任务进行统计;及
    根据统计结果对查勘员标识对应的查勘员级别进行调整。
  6. 一种查勘任务分配系统,包括:
    客户终端,用于获取车险报案信息,将所述车险报案信息上传至服务器,所述车险报案信息包括出险地点;及
    服务器,用于根据所述车险报案信息生成查勘任务;识别所述车险报案信息对应的业务类型;根据所述出险地点查询预设范围内与所述业务类型对应的查勘员标识;将所述查勘任务发送至所述查勘员标识对应的查勘终端。
  7. 根据权利要求6所述的系统,其特征在于,所述服务器还用于对来自不同客户终端的车险报案信息进行大数据分析,得到事故高发地点;根据所述事故高发地点生成对预设范围内的查勘员数量进行调整的提示信息;及将所述提示信息发送至管理终端。
  8. 根据权利要求7所述的系统,其特征在于,所述服务器还用于对所述事故高发地点的车险报案信息的业务类型和数量进行统计;根据业务类型对应的车险报案信息的数量计算查勘员级别对应的查勘员需求数量;获取事故高发地点预设范围内查勘员级别对应的查勘员当前数量;及根据所述查勘员需求数量与所述查勘员当前数量生成对查勘员数量进行调整的提示信息。
  9. 根据权利要求6所述的系统,其特征在于,所述服务器还用于对来自不同客户终端的车险报案信息进行大数据分析,得到高风险出险地点;当接 收到携带所述高风险出险地点的车险报案信息时,生成核实是否骗保的提示信息;及将所述提示信息与所述查勘任务发送至查勘员标识对应的查勘终端。
  10. 根据权利要求6所述的系统,其特征在于,所述查勘员标识具有对应的查勘员级别,所述服务器还用于获取与所述业务类型对应的查勘员级别;根据所述出险地点搜索预设范围内的服务点名称;根据所述服务点名称与所述查勘员级别查询对应的查勘员标识;对所述查勘员标识对应的多个查勘任务进行统计;及根据统计结果对查勘员标识对应的查勘员级别进行调整。
  11. 一种服务器,包括存储器和一个或多个处理器,存储器中储存有计算机可读指令,所述计算机可读指令被处理器执行时,使得一个或多个处理器执行以下步骤:
    接收客户终端上传的车险报案信息,所述车险报案信息包括出险地点;
    根据所述车险报案信息生成查勘任务;
    识别所述车险报案信息对应的业务类型;
    根据所述出险地点查询预设范围内与所述业务类型对应的查勘员标识;及
    将所述查勘任务发送至所述查勘员标识对应的查勘终端。
  12. 根据权利要求11所述的服务器,其特征在于,所述计算机可读指令被处理器执行时,使得一个或多个处理器还执行以下步骤:
    对来自不同客户终端的车险报案信息进行大数据分析,得到事故高发地点;及
    根据所述事故高发地点生成对预设范围内的查勘员数量进行调整的提示信息。
  13. 根据权利要求12所述的服务器,其特征在于,所述计算机可读指令被处理器执行时,使得一个或多个处理器还执行以下步骤:
    对所述事故高发地点的车险报案信息的业务类型和数量进行统计;
    根据业务类型对应的车险报案信息的数量计算查勘员级别对应的查勘员需求数量;
    获取事故高发地点预设范围内查勘员级别对应的查勘员当前数量;及
    根据所述查勘员需求数量与所述查勘员当前数量生成对查勘员数量进行调整的提示信息。
  14. 根据权利要求11所述的服务器,其特征在于,所述计算机可读指令被处理器执行时,使得一个或多个处理器还执行以下步骤:
    对来自不同客户终端的车险报案信息进行大数据分析,得到高风险出险地点;
    当接收到携带所述高风险出险地点的车险报案信息时,生成核实是否骗保的提示信息;及
    将所述提示信息与所述查勘任务发送至查勘员标识对应的查勘终端。
  15. 根据权利要求11所述的服务器,其特征在于,所述查勘员标识具有对应的查勘员级别,所述计算机可读指令被处理器执行时,使得一个或多个处理器还执行以下步骤:
    获取与所述业务类型对应的查勘员级别;根据所述出险地点搜索预设范围内的服务点名称;根据所述服务点名称与所述查勘员级别查询对应的查勘员标识;
    对所述查勘员标识对应的多个查勘任务进行统计;及
    根据统计结果对查勘员标识对应的查勘员级别进行调整。
  16. 一个或多个存储有计算机可读指令的非易失性存储介质,所述计算机可读指令被一个或多个处理器执行时,使得一个或多个处理器执行以下步骤:
    接收客户终端上传的车险报案信息,所述车险报案信息包括出险地点;
    根据所述车险报案信息生成查勘任务;
    识别所述车险报案信息对应的业务类型;
    根据所述出险地点查询预设范围内与所述业务类型对应的查勘员标识;及
    将所述查勘任务发送至所述查勘员标识对应的查勘终端。
  17. 根据权利要求16所述的存储介质,其特征在于,所述计算机可读指令被一个或多个处理器执行时,使得一个或多个处理器还执行以下步骤:
    对来自不同客户终端的车险报案信息进行大数据分析,得到事故高发地点;及
    根据所述事故高发地点生成对预设范围内的查勘员数量进行调整的提示信息。
  18. 根据权利要求17所述的存储介质,其特征在于,所述计算机可读指令被一个或多个处理器执行时,使得一个或多个处理器还执行以下步骤:
    对所述事故高发地点的车险报案信息的业务类型和数量进行统计;
    根据业务类型对应的车险报案信息的数量计算查勘员级别对应的查勘员需求数量;
    获取事故高发地点预设范围内查勘员级别对应的查勘员当前数量;及
    根据所述查勘员需求数量与所述查勘员当前数量生成对查勘员数量进行调整的提示信息。
  19. 根据权利要求16所述的存储介质,其特征在于,所述计算机可读指令被一个或多个处理器执行时,使得一个或多个处理器还执行以下步骤:
    对来自不同客户终端的车险报案信息进行大数据分析,得到高风险出险地点;
    当接收到携带所述高风险出险地点的车险报案信息时,生成核实是否骗保的提示信息;及
    将所述提示信息与所述查勘任务发送至查勘员标识对应的查勘终端。
  20. 根据权利要求16所述的存储介质,其特征在于,所述查勘员标识具有对应的查勘员级别,所述计算机可读指令被一个或多个处理器执行时,使得一个或多个处理器还执行以下步骤:
    获取与所述业务类型对应的查勘员级别;根据所述出险地点搜索预设范围内的服务点名称;根据所述服务点名称与所述查勘员级别查询对应的查勘员标识;
    对所述查勘员标识对应的多个查勘任务进行统计;及
    根据统计结果对查勘员标识对应的查勘员级别进行调整。
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